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#!/usr/bin/env python
import streamlit as st
st.set_page_config(layout="wide")
st.markdown(
"""
# Deep Learning Based Models for Preimplantation Mouse and Human Embryos Based on Single Cell RNA Sequencing
_[Martin Proks](https://orcid.org/0000-0002-8178-3128)\*,
[Nazmus Salehin](https://orcid.org/0000-0002-8155-4296)\*,
[Joshua M. Brickman](https://orcid.org/0000-0003-1580-7491)**_
_\* There authors contributed equally to the work_
_** Corresponding author [[email protected]](mailto:[email protected])_
The rapid growth of single-cell transcriptomic technology has produced an increasing number of
datasets for both embryonic development and _in vitro_ pluripotent stem cell derived models.
This avalanche of data surrounding pluripotency and the process of lineage specification has
meant it has become increasingly difficult to define specific cell types or states and compare
these to _in vitro_ differentiation. Here we utilize a set of deep learning (DL) tools to
integrate and classify multiple datasets. This allows for the definition of both mouse and
human embryo cell types, lineages and states, thereby maximising the information one can garner
from these precious experimental resources. Our approaches are built on recent initiatives for
large scale human organ atlases, but here we focus on the difficult to obtain and process
material that spans early mouse and human development. We deploy similar approaches as the
initiatives building large reference organ atlases, however with a focus on early mammalian
development. Using publicly available data for these stages, we test different deep learning
approaches and develop a model to classify cell types in an unbiased fashion at the same time as
defining the set of genes used by the model to identify lineages, cell types and states. We have
used our models trained on _in vivo_ development to classify pluripotent stem cell models for
both mouse and human development, showcasing the importance of this resource as a dynamic
reference for early embryogenesis.
"""
)
st.image(
"static/Fig-1.v4.3.png",
caption="""
Summary of datasets used to build reference models. a) Schematic overview of mouse
and human preimplantation development. b) Quantification of cells per publication which
were collected for building the mouse (grey) and human (black) reference. c) Computational
schematic of tools used to build and interpret the reference models. d) Gene expression
of canonical markers for each developmental stage in mouse (top) and human (bottom)
preimplantation. e) Reduced dimensional representation of preimplantation mouse (left)
and human (right) datasets. dpf: days post fertilization, E: embryonic day.
""",
)
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